Apparatus, method, and computer program for updating map

ABSTRACT

An apparatus for updating a map includes one or more processors configured to: receive feature data from a vehicle traveling on a predetermined road section for a feature in the road section related to travel of vehicles via a communication circuit, the feature data indicating the position of the feature, measure the accuracy of the position of the feature indicated by feature data obtained by the vehicle, based on the difference between the position of the feature indicated by the received feature data and a reference position of a corresponding feature, determine whether the accuracy satisfies a predetermined accuracy condition, and set contribution of the feature data received from the vehicle to update of map information indicating the position of the feature. The contribution is set lower when the accuracy does not satisfy the accuracy condition than when the accuracy satisfies the accuracy condition.

FIELD

The present invention relates to an apparatus, a method, and a computerprogram for updating a map.

BACKGROUND

High-precision maps to which an autonomous vehicle-driving system refersfor autonomous driving control of a vehicle are required to accuratelyrepresent information on those features on or around roads which relateto travel of vehicles. Thus, a technique to collect data representingfeatures from vehicles actually traveling on roads has been proposed(see International Publication No. 2017/212639).

In the technique disclosed in International Publication No. 2017/212639,a server device includes a storage unit that stores an advanced mapincluding feature information on features. The server device receivesdifference information indicating the difference between featureinformation and an actual feature corresponding to the featureinformation from vehicle-mounted devices each equipped with an externalsensor for measuring features. The server device transmits a raw-datarequest signal for requesting transmission of raw measurement data of anactual feature to a vehicle-mounted device, depending on reliabilitycalculated on the basis of multiple pieces of difference information.

SUMMARY

To record the accurate position of a feature in a map on the basis ofcollected feature-representing data, vehicles that generate thefeature-representing data are required to accurately estimate theposition of the feature. However, the positional accuracy of a featurerepresented in such data generated by some vehicles may be low, or thepositional accuracy may vary from vehicle to vehicle. If collected datarepresenting a feature with low positional accuracy is used for updatinga map, the positional accuracy of the feature represented in the map maydecrease.

It is an object of the present invention to provide an apparatus forupdating a map that can improve the positional accuracy of a featurerepresented in the map.

According to an embodiment, an apparatus for updating a map is provided.The apparatus includes one or more processors configured to: receivefeature data from a vehicle traveling on a predetermined road sectionfor a feature in the road section related to travel of vehicles via acommunication circuit capable of communicating with the vehicle, thefeature data indicating the position of the feature, measure theaccuracy of the position of the feature indicated by feature dataobtained by the vehicle, based on the difference between the position ofthe feature indicated by the received feature data and a referenceposition of a corresponding feature, determine whether the accuracysatisfies a predetermined accuracy condition, and set contribution ofthe feature data received from the vehicle to update of map informationindicating the position of the feature. The contribution is set lowerwhen the accuracy does not satisfy the accuracy condition than when theaccuracy satisfies the accuracy condition.

Preferably, for a model of vehicle, the processors of the apparatusmeasure the accuracy of the position of the feature, based on thedifference between the position of the feature indicated by theindividual feature data received from a plurality of vehicles belongingto the model and the reference position of a corresponding feature, theplurality of vehicles traveling on the predetermined road section, andset the contribution for each model of vehicle, based on the accuracy ofthe position of the feature regarding the model of vehicle.

Preferably, the feature data further includes information indicatingenvironment around the vehicle at the time of generation of the featuredata; the processors of the apparatus measure the accuracy depending onthe environment regarding the vehicle, and set the contributiondepending on the environment, based on the accuracy depending on theenvironment regarding the vehicle.

The processors are preferably further configured to: set correctioninformation for correcting the position of the feature indicated byfeature data obtained by the vehicle. The correction information is setso that the difference between the position of the feature indicated bythe received feature data and the reference position of a correspondingfeature will decrease.

According to another embodiment, a method for updating a map isprovided. The method includes receiving feature data from a vehicletraveling on a predetermined road section for a feature in the roadsection related to travel of vehicles via a communication circuitcapable of communicating with the vehicle, the feature data indicatingthe position of the feature; measuring the accuracy of the position ofthe feature indicated by feature data obtained by the vehicle, based onthe difference between the position of the feature indicated by thereceived feature data and a reference position of a correspondingfeature; determining whether the accuracy satisfies a predeterminedaccuracy condition; and setting contribution of the feature datareceived from the vehicle to update of map information indicating theposition of the feature. The contribution is set lower when the accuracydoes not satisfy the accuracy condition than when the accuracy satisfiesthe accuracy condition.

According to still another embodiment, a non-transitory recording mediumthat stores a computer program for updating a map is provided. Thecomputer program includes instructions causing a computer to execute aprocess including: receiving feature data from a vehicle traveling on apredetermined road section for a feature in the road section related totravel of vehicles via a communication circuit capable of communicatingwith the vehicle, the feature data indicating the position of thefeature; measuring the accuracy of the position of the feature indicatedby feature data obtained by the vehicle, based on the difference betweenthe position of the feature indicated by the received feature data and areference position of a corresponding feature; determining whether theaccuracy satisfies a predetermined accuracy condition; and settingcontribution of the feature data received from the vehicle to update ofmap information indicating the position of the feature. The contributionis set lower when the accuracy does not satisfy the accuracy conditionthan when the accuracy satisfies the accuracy condition.

The apparatus according to the present invention has an advantageouseffect of being able to improve the positional accuracy of a featurerepresented in a map.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 schematically illustrates the configuration of a map updatesystem equipped with an apparatus for updating a map.

FIG. 2 schematically illustrates the configuration of a vehicle.

FIG. 3 illustrates the hardware configuration of a data acquisitiondevice.

FIG. 4 illustrates the hardware configuration of a server, which is anexample of the apparatus for updating a map.

FIG. 5 is a functional block diagram of a processor of the server,related to a map update process.

FIG. 6A illustrates an example of the relationship between the positionof a feature indicated by feature data obtained by a vehicle whosefeature data has relatively high positional accuracy and that of acorresponding reference feature.

FIG. 6B illustrates an example of the relationship between the positionof a feature indicated by feature data obtained by a vehicle whosefeature data has relatively low positional accuracy and that of acorresponding reference feature.

FIG. 7 is an operation flowchart of the map update process.

DESCRIPTION OF EMBODIMENTS

An apparatus for updating a map, a method for updating a map executed bythe apparatus, and a computer program for updating a map will now bedescribed with reference to the attached drawings. Regarding a regionrepresented in a map to be generated or updated, the apparatus collectsdata representing a feature related to travel of vehicles (hereafter,“feature data”) from multiple vehicles that can communicate.

The feature data includes information indicating the position of afeature represented in the data. To estimate the position of a feature,information on parameters of a vehicle-mounted camera for capturingfeatures, such as the height of the mounted position and the imagingdirection of the camera, is used. The parameter information of thecamera is stored in a vehicle-mounted memory, for example, beforeshipment on a vehicle-by-vehicle basis. However, the height of themounted position may vary, for example, because of a change of a tire ofthe vehicle or time-dependent deterioration of its suspension. If theparameter information is not updated despite occurrence of suchvariation, the estimation accuracy of the positions of features willdecrease. The same holds true for the case that the parameterinformation of the camera is incorrectly set. For this reason, toimprove the positional accuracy of features represented in the map, itis desirable to evaluate the estimation accuracy of the positions offeatures for each vehicle.

Thus the apparatus collects feature data including an estimated positionof a feature in a predetermined road section, where the position of thefeature is determined in advance with high accuracy, from individualvehicles traveling on the road section. For each vehicle, the apparatuscalculates the difference between the estimated position of the featureindicated by individual feature data and the position of a correspondingfeature (hereafter, a “reference position”) among features whosepositions are prestored (hereafter, “reference features”). Based on thisdifference, the apparatus measures the accuracy of the position of thefeature indicated by feature data obtained by the vehicle, anddetermines whether the positional accuracy satisfies a predeterminedaccuracy condition. The apparatus then makes contribution to update ofmap information of feature data received from a vehicle whose data haspositional accuracy not satisfying the accuracy condition be lower thancontribution of feature data received from a vehicle whose data haspositional accuracy satisfying the accuracy condition.

Features to be detected include various signposts, various roadmarkings, traffic lights, and other features related to travel ofvehicles.

FIG. 1 schematically illustrates the configuration of a map updatesystem equipped with the apparatus for updating a map. In the presentembodiment, the map update system 1 includes multiple vehicles 2 and aserver 3, which is an example of the apparatus for updating a map. Eachvehicle 2 accesses a wireless base station 5, which is connected, forexample, via a gateway (not illustrated) to a communication network 4connected with the server 3, thereby connecting to the server 3 via thewireless base station 5 and the communication network 4. For simplicity,FIG. 1 illustrates only a single vehicle 2. FIG. 1 also illustrates onlya single wireless base station 5, but the communication network 4 may beconnected with multiple wireless base stations 5. Additionally, theserver 3 may be connected to a traffic information server (notillustrated) that manages traffic information so that they cancommunicate via the communication network.

In the present embodiment, the vehicles 2 have the same configurationand functions concerning collection of feature data. Thus the followingdescribes a single vehicle 2.

FIG. 2 schematically illustrates the configuration of a vehicle 2. Thevehicle 2 includes a camera 11, a GPS receiver 12, a wirelesscommunication terminal 13, and a data acquisition device 14, which areconnected so that they can communicate via an in-vehicle networkconforming to a standard, such as a controller area network. The vehicle2 may further include a navigation device (not illustrated) forsearching for a planned travel route of the vehicle 2 and for navigatingso that the vehicle 2 may travel along the planned travel route.

The camera 11, which is an example of an image capturing unit forcapturing the surroundings of the vehicle 2, includes a two-dimensionaldetector constructed from an array of optoelectronic transducers, suchas CCD or C-MOS, having sensitivity to visible light and a focusingoptical system that forms an image of a target region on thetwo-dimensional detector. The camera 11 is mounted, for example, in theinterior of the vehicle 2 so as to be oriented, for example, to thefront of the vehicle 2. The camera 11 captures a region in front of thevehicle 2 every predetermined capturing period (e.g., 1/30 to 1/10seconds), and generates images of this region. The images obtained bythe camera 11 may be color or grayscale images. The vehicle 2 mayinclude multiple cameras 11 whose imaging directions or focal lengthsdiffer.

Whenever generating an image, the camera 11 outputs the generated imageto the data acquisition device 14 via the in-vehicle network.

The GPS receiver 12 receives GPS signals from GPS satellites atpredetermined intervals, and determines the position of the vehicle 2,based on the received GPS signals. The GPS receiver 12 outputspositioning information indicating the result of determination of theposition of the vehicle 2 based on the GPS signals to the dataacquisition device 14 via the in-vehicle network at predeterminedintervals. The vehicle 2 may include a receiver conforming to asatellite positioning system other than the GPS receiver 12. In thiscase, this receiver determines the position of the vehicle 2.

The wireless communication terminal 13, which is an example of acommunication unit, is a device to execute a wireless communicationprocess conforming to a predetermined standard of wirelesscommunication, and accesses, for example, the wireless base station 5 toconnect to the server 3 via the wireless base station 5 and thecommunication network 4. The wireless communication terminal 13generates an uplink radio signal including, for example, feature datareceived from the data acquisition device 14, and transmits the uplinkradio signal to the wireless base station 5 to transmit, for example,the feature data to the server 3. Additionally, the wirelesscommunication terminal 13 receives a downlink radio signal from thewireless base station 5, and passes, for example, a collectioninstruction from the server 3 included in the radio signal to the dataacquisition device 14 or to an electronic control unit (ECU) (notillustrated) that controls travel of the vehicle 2.

FIG. 3 illustrates the hardware configuration of the data acquisitiondevice. The data acquisition device 14 generates feature data, based onan image generated by the camera 11, and further generates travelinformation of the vehicle 2. To achieve this, the data acquisitiondevice 14 includes a communication interface 21, a memory 22, and aprocessor 23.

The communication interface 21, which is an example of an in-vehiclecommunication unit, includes an interface circuit for connecting thedata acquisition device 14 to the in-vehicle network. In other words,the communication interface 21 is connected to the camera 11, the GPSreceiver 12, and the wireless communication terminal 13 via thein-vehicle network. Whenever receiving an image from the camera 11, thecommunication interface 21 passes the received image to the processor23. Whenever receiving positioning information from the GPS receiver 12,the communication interface 21 passes the received positioninginformation to the processor 23. Additionally, the communicationinterface 21 outputs feature data received from the processor 23 to thewireless communication terminal 13 via the in-vehicle network.

The memory 22 includes, for example, volatile and nonvolatilesemiconductor memories. The memory 22 may further include other storage,such as a hard disk drive. The memory 22 stores various types of dataused in a process related to generation of feature data, which isexecuted by the processor 23 of the data acquisition device 14. Suchdata includes, for example, a road map; identifying information of thevehicle 2; parameters of the camera 11, such as the height of themounted position, the imaging direction, and the angle of view of thecamera 11; and a set of parameters for defining a classifier fordetecting a feature from an image. The road map may be, for example, amap used by the navigation device, and includes information on thepositions and the lengths of road sections included in the regionrepresented in the road map as well as the connection relationshipbetween road sections at individual intersections in this region. Thememory 22 may also stores images received from the camera 11 andpositioning information received from the GPS receiver 12 for a certainperiod. Additionally, the memory 22 stores information indicating atarget region for generating and collecting feature data (hereafter, a“collection target region”) specified in a collection instruction tocollect feature data. The memory 22 may further store computer programsfor various processes executed by the processor 23.

The processor 23 includes one or more central processing units (CPUs)and a peripheral circuit thereof. The processor 23 may further includeanother operating circuit, such as a logic-arithmetic unit, anarithmetic unit, or a graphics processing unit. The processor 23 storesimages received from the camera 11 and positioning information receivedfrom the GPS receiver 12 in the memory 22. Additionally, the processor23 executes the process related to generation of feature data atpredetermined intervals (e.g., 0.1 to 10 seconds) during travel of thevehicle 2.

As the process related to generation of feature data, for example, theprocessor 23 determines whether the position of the vehicle 2 indicatedby positioning information received from the GPS receiver 12 is within acollection target region. When the position of the vehicle is within acollection target region, the processor 23 generates feature data, basedon an image received from the camera 11.

For example, the processor 23 inputs an image received from the camera11 into a classifier that has been trained to detect a detection targetfeature, thereby detecting the feature represented in the inputted image(hereafter simply the “input image”). The processor 23 generatesinformation indicating the type of the detected feature as feature data.As such a classifier, the processor 23 may use, for example, a deepneural network (DNN) that has been trained to detect from an input imagea feature represented in the image. As such a DNN, for example, a DNNhaving a convolutional neural network (CNN) architecture, e.g., SingleShot MultiBox Detector (SSD) or Faster R-CNN, is used. In this case, foreach type of detection target feature (e.g., a lane-dividing line, apedestrian crossing, and a stop line), the classifier calculates aconfidence score indicating how likely the feature is represented in aregion in the input image; the classifier calculates the confidencescore for each of various regions in the input image. The classifierdetermines that the region where the confidence score for a certain typeof feature is not less than a predetermined detection thresholdrepresents this type of feature. The classifier then outputs informationindicating a region including a detection target feature in the inputimage, e.g., a circumscribed rectangle of the detection target feature(hereafter, an “object region”) and information indicating the type ofthe feature represented in the object region. The processor 23 generatesfeature data so as to include the information indicating the type of thefeature represented in the detected object region.

Additionally, the processor 23 identifies the real-space position of afeature indicated by feature data, and includes information indicatingthis position in the feature data. The positions of pixels in an imagecorrespond one-to-one to the directions from the camera 11 to objectsrepresented in the respective pixels. Thus the processor 23 estimatesthe position of a feature represented in an object region in the image,based on the direction from the camera 11 to the position correspondingto the centroid of the object region, the position and the traveldirection of the vehicle 2 at the time of generation of the image usedfor generating the feature data, and the parameters of the camera 11. Tothis end, the processor 23 can use the position indicated by positioninginformation received from the GPS receiver 12 at the timing closest tothe time of generation of the image used for generating the feature dataas the position of the vehicle 2. Alternatively, in the case that theECU (not illustrated) estimates the position of the vehicle 2, theprocessor 23 may obtain information indicating the estimated position ofthe vehicle 2 from the ECU via the communication interface 21. Theprocessor 23 further obtains information indicating the travel directionof the vehicle 2 from the ECU. Alternatively, the processor 23 mayestimate the position of a feature indicated by feature data by“structure from motion (SfM).” In this case, the processor 23 associatesobject regions representing the same feature in two images obtained atdifferent timings with each other, using optical flow. The processor 23can estimate the position of the feature by triangulation, based on thepositions and the travel directions of the vehicle 2 at the times ofacquisition of the two images, the parameters of the camera 11, and thepositions of the object regions in the respective images.

The processor 23 includes, in feature data, the latitude and longitudeindicating the position of the feature represented in the feature dataas information indicating the position of the feature represented in thefeature data. Additionally, the processor 23 refers to the road map toidentify a link that is a road section including the position of thefeature represented in the feature data or a road section closest tothis position. The processor 23 then includes the identification numberof the identified link in the feature data.

The processor 23 further includes the identifying information of thevehicle 2 in feature data. The processor 23 may also include, in thefeature data, information used for estimating the position of thefeature, e.g., the parameters of the camera 11 and the position of thefeature in the image. Additionally, the processor 23 may include, in thefeature data, the position and the travel direction of the vehicle 2 atthe time of generation of the feature data, which are used forestimating the position of the feature, as well as the intensity ofreceived GPS signals used for determining the position of the vehicle 2.The processor 23 may further include, in the feature data, an imageitself generated by the camera 11 or a sub-image obtained by cutting outa region representing a road surface from the image. Whenever generatingfeature data, the processor 23 outputs the generated feature data to thewireless communication terminal 13 via the communication interface 21.In this way, feature data is transmitted to the server 3. The processor23 may transmit the information used for estimating the position of thefeature to the server 3 via the wireless communication terminal 13together with the identifying information of the vehicle 2 separatelyfrom the feature data.

The following describes the server 3, which is an example of theapparatus for updating a map.

FIG. 4 illustrates the hardware configuration of the server 3, which isan example of the apparatus for updating a map. The server 3 includes acommunication interface 31, a storage device 32, a memory 33, and aprocessor 34. The communication interface 31, the storage device 32, andthe memory 33 are connected to the processor 34 via a signal line. Theserver 3 may further include an input device, such as a keyboard and amouse, and a display device, such as a liquid crystal display.

The communication interface 31, which is an example of the communicationunit, includes an interface circuit for connecting the server 3 to thecommunication network 4. The communication interface 31 is configured sothat it can communicate with the vehicles 2 via the communicationnetwork 4 and the wireless base station 5. More specifically, thecommunication interface 31 passes to the processor 34 feature datareceived from the vehicles 2 via the wireless base station 5 and thecommunication network 4. Additionally, the communication interface 31transmits a collection instruction received from the processor 34 to thevehicles 2 via the communication network 4 and the wireless base station5.

The storage device 32, which is an example of a storage unit, includes,for example, a hard disk drive, or an optical recording medium and anaccess device therefor. The storage device 32 stores various types ofdata and information used in a process for collecting map data. Forexample, the storage device 32 stores a map to be updated and areference position of each of one or more reference features in apredetermined road section; the reference position will serve as areference for estimating the positional accuracy of features for eachvehicle 2. Details of the predetermined road section and the referenceposition will be described below. Additionally, the storage device 32stores the identifying information of each vehicle 2 and feature datareceived from each vehicle 2. The storage device 32 may further storeinformation used by each vehicle 2 for estimating the position of afeature and a computer program executed by the processor 34 forexecuting a map update process.

The memory 33, which is another example of a storage unit, includes, forexample, nonvolatile and volatile semiconductor memories. The memory 33temporarily stores various types of data generated during execution ofthe map update process.

The processor 34, which is an example of a control unit, includes one ormore central processing units (CPUs) and a peripheral circuit thereof.The processor 34 may further include another operating circuit, such asa logic-arithmetic unit or an arithmetic unit. The processor 34 executesthe map update process.

FIG. 5 is a functional block diagram of the processor 34, related to themap update process. The processor 34 includes a data receiving unit 41,an accuracy measurement unit 42, a contribution setting unit 43, acorrection information setting unit 44, and a map update unit 45. Theseunits included in the processor 34 are functional modules, for example,implemented by a computer program executed by the processor 34, or maybe dedicated operating circuits provided in the processor 34.

The data receiving unit 41 receives feature data representing eachfeature in a predetermined road section from some of the vehicles 2traveling on the road section via the wireless base station 5, thecommunication network 4, and the communication interface 31. The datareceiving unit 41 stores the received feature data in the memory 33 orthe storage device 32. To determine whether the feature data representsa feature in the predetermined road section, the data receiving unit 41refers to the identification number of the link of the road sectionincluded in the feature data. When the identification number of the linkincluded in the feature data matches that of the link corresponding tothe predetermined road section, the data receiving unit 41 determinesthat the feature data represents a feature in the predetermined roadsection.

As described above, the feature data may include an image itselfgenerated by the camera 11 or a sub-image. In this case, the datareceiving unit 41 may detect the position of a feature by executing, onthe image or the sub-image, the same process as is executed by theprocessor 23 of the data acquisition device 14 for detecting theposition of a feature.

The accuracy measurement unit 42 calculates, for each vehicle 2, thedifference between the position of a feature indicated by individualfeature data of the predetermined road section received from the vehicle2 and the reference position of a corresponding reference feature storedin the server 3. The accuracy measurement unit 42 then measures theaccuracy of the position of a feature indicated by feature data obtainedby the vehicle 2, based on the difference in the position of the featureindicated by the individual feature data.

In the present embodiment, the predetermined road section may be a roadsection where the position of each feature therein is determined withhigh accuracy. For example, the predetermined road section may be a roadsection in an expressway regarding which it is confirmed that thepositional accuracy of each feature represented in the map is high,e.g., it is confirmed that road construction has not been performedsince the last update of the map. In the case that the position of eachfeature in the map is expressed as a probability distribution ofreliability of the position, the predetermined road section may be asection where the extent of the probability distribution is not greaterthan a certain extent for each feature and the accuracy of satellitepositioning is not less than a predetermined accuracy threshold. Theextent of the probability distribution is expressed as, for example,variance values in predetermined directions (e.g., the lengthwisedirection of the road section and the direction perpendicular to thelengthwise direction).

For individual feature data of the predetermined road section receivedfrom a vehicle 2 of interest, the accuracy measurement unit 42determines a reference feature of the same type as and closest to thefeature represented in the feature data as a reference featurecorresponding to the feature represented in the feature data. For eachfeature represented in the individual feature data of the predeterminedroad section received from the vehicle 2 of interest, the accuracymeasurement unit 42 then calculates the distance and the direction fromthe reference position of the corresponding reference feature to theposition of the feature. The accuracy measurement unit 42 calculates theaverage of the absolute values or the root mean square of distancescalculated for the individual feature data as an accuracy indexindicating the positional accuracy of feature data obtained by thevehicle 2 of interest. In the case that the position of each feature isexpressed as a probability distribution of reliability of the position,the distance from a reference position to the position of a featureindicated by feature data may be expressed as a Mahalanobis distance.For the individual feature data, the accuracy measurement unit 42further calculates the angle between the travel direction of the vehicle2 at the time of generation of the feature data and the direction fromthe reference position of the reference feature to the position of thefeature indicated by the feature data (hereafter, the “angle error”).The accuracy measurement unit 42 uses the angle error and the distancecalculated for the individual feature data as correction indices forcorrecting the position of a feature regarding the vehicle 2 ofinterest. The accuracy measurement unit 42 can calculate accuracyindices and correction indices for the respective vehicles 2 byexecuting the above-described process for each vehicle 2.

FIG. 6A illustrates an example of the relationship between the positionof a feature indicated by feature data obtained by a vehicle 2 whosefeature data has relatively high positional accuracy and that of acorresponding reference feature. FIG. 6B illustrates an example of therelationship between the position of a feature indicated by feature dataobtained by a vehicle 2 whose feature data has relatively low positionalaccuracy and that of a corresponding reference feature. In FIGS. 6A and6B, the reference feature is a road marking depicted by solid lines.

As illustrated in FIG. 6A, when the positional accuracy of feature datais relatively high, the position of a corresponding feature 602indicated by feature data is sufficiently close to the referenceposition of a reference feature 601. In contrast, as illustrated in FIG.6B, when the positional accuracy of feature data is relatively low, thedistance between the reference position of the reference feature 601 andthe position of the corresponding feature 602 indicated by feature datais longer.

The accuracy measurement unit 42 notifies the contribution setting unit43 of the accuracy index calculated for each vehicle 2. The accuracymeasurement unit 42 also notifies the correction information settingunit 44 of the accuracy index and the correction indices calculated foreach vehicle 2.

The contribution setting unit 43 sets, for each vehicle 2, contributionof feature data received from the vehicle 2 to update of the map, basedon the accuracy index received from the accuracy measurement unit 42. Inthe present embodiment, for each vehicle 2, contribution of feature datareceived from the vehicle 2 when the positional accuracy of a featureincluded in feature data, which is indicated by the accuracy index, doesnot satisfy an accuracy condition, is set lower than contribution offeature data received from the vehicle 2 when the positional accuracysatisfies the accuracy condition. Thus, contribution of feature datareceived from a vehicle whose data has positional accuracy satisfyingthe accuracy condition will be higher than contribution of feature datareceived from another vehicle whose data has positional accuracy notsatisfying the accuracy condition. As a result, the position of afeature indicated by feature data received from a vehicle whose data haspositional accuracy satisfying the accuracy condition will beparticularly reflected in the map, which improves the positionalaccuracy of features represented in the map.

The accuracy condition is set, for example, so that the positional errorof features represented in the map updated using feature data whosepositional accuracy satisfies the accuracy condition will be within atolerable range for autonomous driving control of a vehicle. In the casethat the accuracy index is expressed as the average of the absolutevalues or the root mean square of distances between features representedin individual feature data and corresponding reference features asdescribed above, the accuracy condition is that the value of theaccuracy index is not greater than a tolerable positional error offeatures (e.g., ten to several tens of centimeters) or the valuecorresponding to its square. In the case that the position of eachfeature in the map is expressed as a probability distribution ofreliability of the position, the accuracy condition may be that thevalue of the accuracy index is not greater than a predetermined distancethreshold expressed as a Mahalanobis distance.

The contribution setting unit 43 assigns a first contribution (e.g.,1.0) to some of the vehicles 2 whose feature data has positionalaccuracy satisfying the accuracy condition. The contribution settingunit 43 assigns a second contribution (e.g., 0.0 to 0.5), which is lowerthan the first contribution, to the other vehicles 2 whose feature datahas positional accuracy not satisfying the accuracy condition. Thecontribution setting unit 43 may decrease the second contribution as thedifference between the value of the accuracy index and the accuracycondition increases.

The contribution setting unit 43 notifies the map update unit 45 of thecontribution set for each vehicle 2.

The correction information setting unit 44 sets, for each vehicle 2whose data has positional accuracy not satisfying the accuracycondition, correction information for correcting the position of afeature of feature data received from the vehicle 2.

The positional accuracy of feature data depends on the accuracy ofparameters used for estimating the position of a feature indicated byfeature data. In the present embodiment, the real-space position of afeature is estimated on the basis of the position of the feature in animage generated by the camera 11 mounted on the vehicle 2 and theposition of the vehicle 2. For this reason, parameters of the camera 11,such as the imaging direction and the height of the mounted position ofthe camera 11, and the intensity of GPS signals affect the positionalaccuracy of the feature data. In particular, the more the parametervalues of the camera 11 stored in the data acquisition device 14 of thevehicle 2 deviate from their actual values, the more the positionalaccuracy of feature data decreases. For example, as described above, theheight of the mounted position of the camera 11 may vary because of achange of a tire of the vehicle 2 or time-dependent deterioration of itssuspension, resulting in deviation of the parameters values of thecamera 11 stored in the data acquisition device 14 from their actualvalues.

When the parameters of the camera 11 values, such as the imagingdirection or the height of the mounted position of the camera 11,deviate from their actual values, the position of a feature indicated byfeature data will deviate from its actual position in the direction andby the distance depending on the deviation. Thus the correctioninformation setting unit 44 sets the correction information so as todecrease the difference between the position of a feature indicated byfeature data of the predetermined road section and the referenceposition of a corresponding reference feature. In this example, thecorrection information setting unit 44 calculates the average of theangle errors and that of the distances expressed as the correctionindices regarding the individual feature data. The correctioninformation setting unit 44 then sets, in the correction information,the angle opposite to the average of the angle errors relative to thetravel direction of the vehicle 2 as well as the average of thedistances.

The correction information setting unit 44 notifies the map update unit45 of the correction information set for the vehicles 2 whose data haspositional accuracy not satisfying the accuracy condition.

The map update unit 45 generates or updates the map read from thestorage device 32, based on feature data collected from the vehicles 2.For example, among the features represented by individual feature data,the map update unit 45 selects features of the same type located withina predetermined range as feature data representing the same feature. Inthe case that the position of each feature is expressed as a probabilitydistribution of reliability of the position, the predetermined range maybe expressed as a Mahalanobis distance. The map update unit 45 weightsthe positions of the feature included in the individual feature datarepresenting the same feature with the contribution set for the vehicles2 that have generated the feature data, averages these positions, andidentifies the obtained position as the position of the feature. Foreach feature whose position is identified, the map update unit 45includes information indicating the type and the identified position ofthe feature in the map to generate or update the map.

Regarding feature data received from the vehicles 2 whose data haspositional accuracy not satisfying the accuracy condition, the mapupdate unit 45 corrects the positions of the feature, using thecorrection information set for the vehicles 2, and then uses thecorrected positions for obtaining the weighted average. Morespecifically, the map update unit 45 corrects the positions of thefeature included in the feature data by moving theses positions in thedirection and by the distance indicated by the correction informationrelative to the travel direction of the vehicle 2 included in thefeature data.

FIG. 7 is an operation flowchart of the map update process in the server3. The processor 34 of the server 3 executes the map update process inaccordance with this operation flowchart at predetermined intervals.

The data receiving unit 41 of the processor 34 receives feature data ofa predetermined road section from each vehicle 2, and stores the featuredata in the storage device 32 (step S101). For each vehicle 2, theaccuracy measurement unit 42 of the processor 34 measures the accuracyof the position of a feature indicated by feature data, based on thedifference between the position of the feature indicated by the receivedindividual feature data and the reference position of a correspondingreference feature (step S102).

The contribution setting unit 43 of the processor 34 sets contributionfor each vehicle 2 so that contribution of feature data received from avehicle 2 whose feature data has positional accuracy not satisfying theaccuracy condition will be lower than contribution of feature datareceived from a vehicle 2 whose data has positional accuracy satisfyingthe accuracy condition (step S103). Additionally, for each vehicle 2whose data has positional accuracy not satisfying the accuracycondition, the correction information setting unit 44 of the processor34 sets correction information so that the difference between theposition of the feature indicated by the individual feature data of thepredetermined road section and the reference position of thecorresponding reference feature will decrease (step S104).

The map update unit 45 of the processor 34 identifies the position ofthe feature indicated by the feature data received from the vehicles 2,using the contribution set for each vehicle 2 and the correctioninformation set for the vehicles 2 whose data has positional accuracynot satisfying the accuracy condition (step S105). The map update unit45 then includes the identified position and the type of the feature inthe map to generate or update the map (step S106). Thereafter, theprocessor 34 terminates the map update process.

As has been described above, the apparatus for updating a map collectsfeature data including an estimated position of a feature in apredetermined road section, where a reference position of the feature isdetermined, from individual vehicles traveling on the road section. Foreach vehicle, the apparatus measures the accuracy of the position of thefeature indicated by feature data obtained by the vehicle, based on thedifference between the estimated position of the feature indicated byindividual feature data and the reference position of a correspondingfeature, and determines whether the positional accuracy satisfies apredetermined accuracy condition. The apparatus then makes contributionto update of map information of feature data received from a vehiclewhose data has positional accuracy not satisfying the accuracy conditionbe lower than contribution of feature data received from a vehicle whosedata has positional accuracy satisfying the accuracy condition. In thisway, the apparatus decreases contribution to the map to be generated orupdated of feature data received from a vehicle whose feature data haslow positional accuracy, and thus can improve the positional accuracy offeatures represented in the map.

It is supposed that two or more vehicles 2 of the same model areequipped with a camera of the same type mounted at the same position soas to capture images in the same direction. Thus, according to amodified example, the parameters of the camera 11 may be set on avehicle model by vehicle model basis rather than on a vehicle-by-vehiclebasis. In this case, the data acquisition device 14 of each vehicle 2may include identifying information of the model of the vehicle 2 infeature data. Alternatively, the storage device 32 of the server 3 maystore the identifying information of the models of the respectivevehicles 2 together with the identifying information of the vehicles 2.

In this case, the accuracy measurement unit 42 executes, for each modelof vehicle, a process similar to that in the embodiment on feature dataof the predetermined road section received from vehicles belonging tothe model to measure the positional accuracy for each model. Thecontribution setting unit 43 also executes a process similar to that inthe embodiment for each model of vehicle to set contribution for eachmodel. Additionally, the correction information setting unit 44 executesa process similar to that in the embodiment for each model of vehiclewhose data has positional accuracy not satisfying the accuracy conditionto set correction information for the model of vehicle.

According to this modified example, the apparatus for updating a mapsets contribution and correction information on a vehicle model byvehicle model basis rather than on a vehicle-by-vehicle basis, and thuscan facilitate management of the contribution and the correctioninformation.

The condition of the environment around a vehicle 2 at the time ofgeneration of feature data may affect the positional accuracy offeatures. For example, a decrease in intensity of received GPS signalscaused by the environment around by a vehicle 2 decreases the estimationaccuracy of the position of the vehicle 2, which also decreases thepositional accuracy of features. Thus, in the above-described embodimentor modified examples, the data acquisition device 14 provided on eachvehicle 2 may include information indicating the environment around thevehicle 2 at the time of generation of feature data (e.g., weather andatmospheric temperature) in the feature data. In this case, the dataacquisition device 14 obtains the information indicating the environmentaround the vehicle 2, based on, for example, a sensor signal from atemperature sensor provided on the vehicle 2 or information on theweather around the current position of the vehicle 2 received via thewireless communication terminal 13. For each vehicle 2, the accuracymeasurement unit 42 of the apparatus executes a process similar to thatin the embodiment on feature data of the predetermined road sectionreceived from the vehicle on an environmental condition by environmentalcondition basis to measure the positional accuracy depending on theenvironment regarding the vehicle. For each vehicle 2, the contributionsetting unit 43 also executes a process similar to that in theembodiment on an environmental condition by environmental conditionbasis to set contribution depending on the environment for the vehicle.Additionally, the correction information setting unit 44 executes aprocess similar to that in the embodiment for each vehicle andenvironmental condition in which the positional accuracy does notsatisfy the accuracy condition, to set correction information dependingon the environment for the vehicle.

According to this modified example, the apparatus for updating a mapsets contribution and correction information in view of theenvironmental condition as well as the parameters of the camera of eachvehicle, and thus can further improve the positional accuracy offeatures represented in the map.

In the above-described embodiment or modified examples, the process ofeither the contribution setting unit 43 or the correction informationsetting unit 44 may be omitted. When the process of the contributionsetting unit 43 is omitted, the same contribution may be set for eachvehicle, model of vehicle, or environmental condition regardless of thepositional accuracy of features. Even in this case, the apparatus canimprove the positional accuracy of features represented in the mapbecause the positions of features are corrected, using the correctioninformation, regarding feature data obtained from a vehicle or under anenvironmental condition in which the positional accuracy not satisfyingthe accuracy condition. Even when the process of the correctioninformation setting unit 44 is omitted, the apparatus can improve thepositional accuracy of features represented in the map because thecontribution of feature data obtained from a vehicle or under anenvironmental condition in which the positional accuracy does notsatisfy the accuracy condition is set relatively low.

The computer program for causing a computer to achieve the functions ofthe units included in the processor of the apparatus for updating a mapaccording to the embodiment or modified examples may be provided in aform recorded on a computer-readable recording medium. Thecomputer-readable recording medium may be, for example, a magneticrecording medium, an optical recording medium, or a semiconductormemory.

As described above, those skilled in the art may make variousmodifications according to embodiments within the scope of the presentinvention.

What is claimed is:
 1. An apparatus for updating a map, comprising: oneor more processors configured to: receive feature data from a vehicletraveling on a predetermined road section for a feature in the roadsection related to travel of vehicles via a communication circuitcapable of communicating with the vehicle, the feature data indicatingthe position of the feature, measure the accuracy of the position of thefeature indicated by feature data obtained by the vehicle, based on thedifference between the position of the feature indicated by the receivedfeature data and a reference position of a corresponding feature,determine whether the accuracy satisfies a predetermined accuracycondition, and set contribution of the feature data received from thevehicle to update of map information indicating the position of thefeature, the contribution being set lower when the accuracy does notsatisfy the accuracy condition than when the accuracy satisfies theaccuracy condition.
 2. The apparatus according to claim 1, wherein for amodel of vehicle, the processors measure the accuracy of the position ofthe feature, based on the difference between the position of the featureindicated by the individual feature data received from a plurality ofvehicles belonging to the model and the reference position of acorresponding feature, the plurality of vehicles traveling on thepredetermined road section, and set the contribution for the model ofvehicle, based on the accuracy of the position of the feature regardingthe model of vehicle.
 3. The apparatus according to claim 1, wherein thefeature data further includes information indicating environment aroundthe vehicle at the time of generation of the feature data, theprocessors measure the accuracy depending on the environment regardingthe vehicle, and set the contribution depending on the environment,based on the accuracy depending on the environment regarding thevehicle.
 4. The apparatus according to claim 1, wherein the processorsare further configured to set correction information for correcting theposition of the feature indicated by feature data obtained by thevehicle, the correction information being set so that the differencebetween the position of the feature indicated by the received featuredata and the reference position of a corresponding feature willdecrease.
 5. A method for updating a map, comprising: receiving featuredata from a vehicle traveling on a predetermined road section for afeature in the road section related to travel of vehicles via acommunication circuit capable of communicating with the vehicle, thefeature data indicating the position of the feature; measuring theaccuracy of the position of the feature indicated by feature dataobtained by the vehicle, based on the difference between the position ofthe feature indicated by the received feature data and a referenceposition of a corresponding feature; determining whether the accuracysatisfies a predetermined accuracy condition; and setting contributionof the feature data received from the vehicle to update of mapinformation indicating the position of the feature, the contributionbeing set lower when the accuracy does not satisfy the accuracycondition than when the accuracy satisfies the accuracy condition.
 6. Anon-transitory recording medium that stores a computer program forupdating a map, the computer program causing a computer to execute aprocess comprising: receiving feature data from a vehicle traveling on apredetermined road section for a feature in the road section related totravel of vehicles via a communication circuit capable of communicatingwith the vehicle, the feature data indicating the position of thefeature; measuring the accuracy of the position of the feature indicatedby feature data obtained by the vehicle, based on the difference betweenthe position of the feature indicated by the received feature data and areference position of a corresponding feature; determining whether theaccuracy satisfies a predetermined accuracy condition; and settingcontribution of the feature data received from the vehicle to update ofmap information indicating the position of the feature, the contributionbeing set lower when the accuracy does not satisfy the accuracycondition than when the accuracy satisfies the accuracy condition.